Project Details
Description
ABSTRACT
The use of immunotherapy to treat cancer continues to generate hope and excitement among those involved in
cancer care and research. However, our inability to explain why some patients do not respond to
immunotherapy, combined with our inability to identify early response or predict the responders, poses serious
challenges in this field. Currently, biopsies serve as the most informative way to assess the immunological
activity within a cancerous area, but we are spatially and temporally limited in the number of biopsies we can
obtain from patients, especially in cases of brain cancer. Clear evidence of tumor-immune environment
heterogeneity across patients suggests that we will have to use an individualized approach in order to
accurately assess patient tumor’s specific immune environment and the evolution of these complex systems.
We propose to use computational modeling and artificial intelligence to bridge the spatial scales of the cellular
content comprising each MRI at the voxel level, but also to bridge the temporal scales. We will focus on the
most cellular immune population in glioblastoma, microglia/macrophages, that constitute as much as 50% of
the cellular content of tumor specimens. By fusing MRI with the biological heterogeneity found in image-
localized biopsies through such radiomics approaches provides an opportunity to individualize our
understanding of the the tumor-immune environment, broadly benefiting scientists across the fields of oncology
and immunology. In addition to providing a deeper understanding of the tumor at every imaging time point, the
radiomics maps can also be used to parameterize dynamic mechanistic models of tumor growth to allow for
prediction of future dynamics. These spatio-temporal models allow us to test hypotheses about causal
relationships between different cell types and microenvironmental factors, as well as to verify whether the
radiomics maps provide early dynamic insights into tumor response that can impact clinical decision making.
Status | Active |
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Effective start/end date | 3/1/21 → 2/28/25 |
Funding
- National Cancer Institute: $10,574.00
- National Cancer Institute: $654,652.00
- National Cancer Institute: $600,426.00
- National Cancer Institute: $81,303.00
- National Cancer Institute: $90,449.00
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